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首页> 外文期刊>Combustion and Flame >Chemical kinetic model reduction through species-targeted global sensitivity analysis (STGSA)
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Chemical kinetic model reduction through species-targeted global sensitivity analysis (STGSA)

机译:通过物种靶向全局敏感性分析(STGSA)减少化学动力学模型

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摘要

The uncertainty of the rate coefficients of elementary reactions in detailed chemical kinetic mechanisms can affect the predicted species concentrations and global properties. The size of reduced mechanisms generated by reduction methods, such as directed relation graph (DRG), can also be greatly affected by the uncertainties in the rate coefficients, because these methods eliminate species by comparing contributions of the production rates of important species from other species. In order to obtain the optimum reduced mechanism in the uncertainty domain of reaction rate parameters, the species-targeted global sensitivity analysis (STGSA) method is proposed to measure the importance of species in kinetic mechanisms and to simplify them by considering the input uncertainties. The demonstrations are performed for the ethylene oxidation mechanism using the USC-Mech II with 111 species and the n-heptane oxidation mechanism using the JetSurf (version 1.0) with 194 species. It is found that STGSA can accurately identify the redundant global species and generate more compact reduced mechanisms compared with the DRG-based methods, resulting in a 33-species reduced mechanism for ethylene oxidation and a 37-species reduced mechanism for n-heptane oxidation. These reduced mechanisms show accurate predictions for the ignition delay times and laminar flame speeds over a wide range of operating conditions. (C) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译:详细化学动力学机制中基本反应的速率系数的不确定性会影响预测物种浓度和全局性质。减少方法产生的减少机制的规模,例如指向关系图(DRG),也可以大大影响速率系数中的不确定性,因为这些方法通过比较来自其他物种的重要种类的生产率的贡献来消除物种。为了获得反应速率参数的不确定性结构域中的最佳减少机制,提出了物种靶向的全局敏感性分析(STGSA)方法来测量物种在动力学机制中的重要性,并通过考虑输入的不确定性来简化它们。使用具有111种的USC-MECHI II和使用Jetsure(1.0版)的USC-MECH II使用194种,对乙烯氧化机制进行示范。结果发现,与基于DRG的方法相比,STGSA可以准确地识别冗余的全局物种,并产生更紧凑的减少机制,导致乙烯氧化的33种减少机制,并为正庚烷氧化的37种减少机制。这些减少的机制显示了对点火延迟时间和层流火焰在各种操作条件下的精确预测。 (c)2020燃烧研究所。由elsevier Inc.出版的所有权利保留。

著录项

  • 来源
    《Combustion and Flame 》 |2021年第2期| 73-82| 共10页
  • 作者单位

    Harbin Inst Technol Sch Energy Sci & Engn Harbin 150001 Heilongjiang Peoples R China;

    Harbin Inst Technol Sch Energy Sci & Engn Harbin 150001 Heilongjiang Peoples R China;

    Tsinghua Univ Ctr Combust Energy Beijing 100084 Peoples R China|Tsinghua Univ Dept Energy & Power Engn Beijing 100084 Peoples R China|Tsinghua Univ Key Lab Thermal Sci & Power Engn MOE Int Joint Lab Low Carbon Clean Energy Innovat Beijing 100084 Peoples R China;

    Princeton Univ Dept Mech & Aerosp Engn Princeton NJ 08544 USA;

    Princeton Univ Dept Mech & Aerosp Engn Princeton NJ 08544 USA;

    Harbin Inst Technol Sch Energy Sci & Engn Harbin 150001 Heilongjiang Peoples R China;

    Tsinghua Univ Ctr Combust Energy Beijing 100084 Peoples R China|Tsinghua Univ Dept Energy & Power Engn Beijing 100084 Peoples R China|Tsinghua Univ Key Lab Thermal Sci & Power Engn MOE Int Joint Lab Low Carbon Clean Energy Innovat Beijing 100084 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    STGSA; DRG; Sobol sensitivity indices; Mechanism reduction; Uncertainty analysis;

    机译:STGSA;DRG;SOBOL敏感性指数;减少机制;不确定性分析;
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